Exam P 5-Week Bootcamp For September 2021 Sitting

Register Today!

Join a 5-week intensive program offering weekly live and interactive lectures of key exam syllabus topics and related problem solving review plus the opportunity for each student to receive individual tutoring assistance and support from the instructor throughout the program.

Charles Major has accumulated over 40 years of experience in leading students to academic and actuarial exam success.  Professor Major leads classes at both New York University and University of North Florida for students preparing for their actuarial exams, specializing in Exams P, FM, and IFM.  Professor Major holds a BS in Math and Statistics from University of New Hampshire, MS in Math, Statistics, and Operations Research for Finance from New York University, and is working towards a PhD in Math and Science from University of New Hampshire.

The Exam P 5-Week Bootcamp provides the following:

  1. Weekly 2 hour live lecture integrating concept building with significant focus on problem solving improvement.
  2. Open Forum immediately following each weekly lecture in which students can ask Professor Major questions related to any topic/problem solving
  3. Weekly problem sets to reinforce material reviewed during live lectures
  4. Weekly Online Office Hours with Professor Major
  5. Mini-Sessions in which students can schedule private help with Professor Major
  6. Q & A Email Correspondence in which students can email Professor Major questions with quick reply back
  7. Students can join The Exam P Discussion Group open only to program members to communicate with each other and Professor Major
  8. All weekly lectures recorded and available to students


Live Classes & Subjects

Lecture 1: 8/22
10:00 AM - 12:00 PM EST
1. Conditional Probability
2. Bayes Theorem
3. Combinatorics
4. Discrete Probability Distributions, Mean, Expectation, MGF
a. Binomial
b. Poisson
c. Geometric
d. Hypergeometric
e. Negative Binomial
Lecture 2: 8/29
10:00 AM - 12:00 PM EST
1. Continuous Probability Distributions, Mean, Expectation, MGF
a. Normal Distribution
b. Inverse Normal Distribution
c. Uniform Distribution
d. Exponential Distribution
e. Beta Distribution
f. Gamma Distribution
Lecture 3: 9/5
10:00 AM - 12:00 PM EST
1. Expectation, Variance Convolution, Univariate, Multivariate
2. Conditional Expectation
3. General Law of Expectation
4. Conditional Variance
5. Covariance
6. Application of Multivariate Distributions
Lecture 4: 9/8
7:00 PM - 9:00 PM EST
1. Risk Management Applications
a. Loss Distribution and Insurance
b. Partial Insurance Coverage
c. Policy Limits Applications
d. Proportional Insurance
e. Individual Risk Modeling
f. Aggregate Claims Processing
g. Loss Distributions by Conditioning
Lecture 5: 9/12
10:00 AM - 12:00 PM EST
1. Set Theory and Venn Diagrams
2. Normal Approximation for Discrete Distributions

Join The Exam P 5-Week Bootcamp and Position Yourself to Pass Exam P